AI Software Engineer
Listed on 2026-06-20
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Software Development
AI Engineer (Applied/Software)
At BGBx
, we’re driven by a simple idea: breakthrough thinking creates breakthrough impact. As an independent commercial solutions partner to pharmaceutical and life science companies, we bring together strategists, scientists, communicators, creatives, technologists, and data experts to tackle some of healthcare’s most important challenges.
Our teams work across consulting and communications to help clients shape strategy, launch innovations, engage stakeholders, and drive meaningful results throughout the product lifecycle. The work is complex, fast‑moving, and deeply connected to improving lives, creating opportunities for curious minds to make a real difference every day.
If you’re energized by collaboration, inspired by innovation, and motivated by work that matters, you’ll find a place to grow, contribute, and make a meaningful impact at BGBx.
AI Software Engineer POSITION SUMMARYThe AI Software Engineer designs, develops, and improves the AI‑enabled applications, agents, copilots, integrations, and workflow automations that bring BGB’s AI operating vision to life. This role converts product requirements and business workflows into working software that supports operational efficiency, knowledge management, content workflows, claims reuse, strategic planning, production standardization, and measurement. The engineer is responsible for building solutions that are usable, maintainable, governed, and ready to scale across agency teams.
The AI Software Engineer designs and builds the internal AI applications, agents, skills, and integrations that turn strategy into repeatable execution.
Primary MissionCreate production‑ready AI solutions that automate high‑value workflows and improve speed, quality, consistency, and reuse.
Key PartnersAI Product Manager, Agentic Platform Architect, UX/UI, Medical, Strategy, Editorial, Production, Analytics, functional SMEs, implementation partners.
Success MeasuresWorking agents and apps, workflow cycle‑time reduction, adoption, reusable components, quality checks, measurable efficiency, and safe handoff to teams.
Responsibilities- Build and maintain internal AI‑enabled applications, agents, copilots, workflow automations, GPT skills, and reusable service components.
- Develop core capabilities connected to the AI operating model, including Orchestration Engine workflows, Claims Library functionality, Cortex/memory use cases, 3D Science strategic tools, editorial/copy assistance, and production automation.
- Develop integrations between LLM platforms, enterprise systems, data sources, content repositories, project workflows, design tools, analytics platforms, and knowledge bases.
- Build RAG systems, prompt orchestration workflows, AI service layers, embedding pipelines, structured output patterns, and reusable agent tools.
- Develop APIs, middleware, backend services, event triggers, data connectors, and automation logic that allow agents to operate across systems safely and consistently.
- Implement guardrails, validation logic, hallucination checks, source attribution, human‑in‑the‑loop review, approval routing, permissions, and governance controls.
- Optimize prompt workflows, model selection, latency, performance, reliability, cost efficiency, and token usage for production‑level AI workflows.
- Collaborate with Product, UX, SMEs, and end users to prototype, test, refine, and scale AI solutions that solve real workflow needs.
- Participate in architecture reviews, sprint planning, code reviews, QA processes, documentation, and release management.
- Maintain reusable code libraries, prompt templates, evaluation scripts, agent patterns, and technical documentation that accelerate future AI development.
- 5+ years of software engineering experience, preferably in enterprise applications, automation platforms, data‑driven products, or AI‑enabled tools.
- Experience using AI/LLM APIs such as OpenAI, Anthropic, Azure OpenAI, or comparable platforms.
- Experience building APIs, middleware, backend services, cloud‑based applications, and secure integrations with third‑party systems.
- Familiarity with vector databases, embeddings, RAG architecture, agent frameworks, prompt engineering,…
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